Language independent connectivity strength features for phrase pivot statistical machine translation

Ahmed El Kholy, Nizar Habash, Gregor Leusch, Evgeny Matusov, Hassan Sawaf

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

An important challenge to statistical machine translation (SMT) is the lack of parallel data for many language pairs. One common solution is to pivot through a third language for which there exist parallel corpora with the source and target languages. Although pivoting is a robust technique, it introduces some low quality translations. In this paper, we present two language-independent features to improve the quality of phrase-pivot based SMT. The features, source connectivity strength and target connectivity strength reflect the quality of projected alignments between the source and target phrases in the pivot phrase table. We show positive results (0.6 BLEU points) on Persian-Arabic SMT as a case study.

Original languageEnglish (US)
Title of host publicationShort Papers
PublisherAssociation for Computational Linguistics (ACL)
Pages412-418
Number of pages7
ISBN (Print)9781937284510
StatePublished - 2013
Event51st Annual Meeting of the Association for Computational Linguistics, ACL 2013 - Sofia, Bulgaria
Duration: Aug 4 2013Aug 9 2013

Publication series

NameACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference
Volume2

Other

Other51st Annual Meeting of the Association for Computational Linguistics, ACL 2013
CountryBulgaria
CitySofia
Period8/4/138/9/13

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language

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